ValueError: Tensor conversion requested dtype float32 for Tensor with dtype int32

Question

I get following error

ValueError: Tensor conversion requested dtype float32 for Tensor with dtype int32: 'Tensor("Placeholder_1:0", shape=TensorShape([Dimension(128), Dimension(2)]), dtype=int32)'

when I try to calculate cross entropy loss

losses = tf.nn.softmax_cross_entropy_with_logits(scores, input_y)

I use Python 3.4.3.

Any ideas why?

Subrogation

Answer 1

It sounds like you have defined input_y—which I am assuming is a tf.placeholder()—as having type tf.int32. Either change this to tf.float32 or add a cast: tf.cast(input_y, tf.float32) or tf.to_float(input_y).

Varuna

i can't find cast or to_float in tflearn, which module do we have to import? – Soubise

tf.cast() and tf.to_float() are TensorFlow functions, so you'd get them using import tensorflow as tf. – Varuna

you can also define the datatype while assignment dtype=tf.float32 – Coarse

Answer 2

I replaced %tensorflow_version 1.x in my code with !pip install tensorflow==1.15.5 and the error disappeared. Not limited to just version 1.15.5, it works for some other TensorFlow version 1s as well.

Capitation